Designing an automated intelligent production management system

Abstract

This article is devoted to the design of an automated intelligent production management system, which is an urgent area in the context of the rapid development of industry 4.0. The introduction describes the need to increase the efficiency and flexibility of production processes through the introduction of intelligent solutions that can quickly respond to changes in market conditions and technological challenges. The research problem is the integration of modern control methods, automation and artificial intelligence to optimize the operation of production lines. The research methods are based on systemic and cognitive approaches in the development of the architecture of an automated system. Mathematical modeling, simulation analysis methods, and machine learning algorithms were used, which made it possible to develop a prototype of a managed platform that combines elements of planning, monitoring, and process diagnostics. The article describes in detail the design stages, starting from conceptual modeling to integration testing, and also provides a comparison of traditional solutions with the proposed methodology in terms of such indicators as reaction speed, control accuracy, and system adaptability to external influences. The results of the study demonstrate a significant improvement in production parameters when using an intelligent automated system. Experimental confirmation of the prototype's operability revealed a 25-30% increase in control efficiency due to process optimization and lower equipment maintenance costs. In addition, the system has shown high resilience to emergency situations and the ability to scale for use on various production lines. The discussion of the results focuses on the practical significance of the proposed methodology for modernizing production in the context of digital transformation. The prospects for further research aimed at increasing the level of system autonomy and integration with cloud platforms for real-time data processing are analyzed. In conclusion, it is concluded that the developed automated intelligent production management system has a high potential for implementation within the framework of industrial automation, which can contribute to the transition of enterprises to a new level of production efficiency and innovative development.